Hybrid organic inorganic perovskites are a promising highly efficient photovoltaic material that can be solution processed at low temperatures enabling an inexpensive solution to rising renewable energy demands with high-volume, scalable manufacturing of solar cells. Small scale perovskite devices are successful using spin coating; however, this needs to translate to larger scale deposition systems such as roll-to-roll slot die printing. Understanding the crystallization and morphology dependence of these materials is essential to enabling slot-die coated perovskite films on scalable systems and transitioning this technology to the market. In order to model crystallization rates of printed layers, we used in-situ optical and photoluminescence microscopy during printing of perovksite films to determine crystal growth rates and evaluate perovskite conversion. Printing parameters were manipulated through variation of temperature, atmospheric conditions, ink recipes, and substrate surface energy generating a model to achieve desired grain size and morphology of the perovskite layer across an array of relevant potential perovskite photovoltaic device stacks. Following classical models, we determined the necessary parameters to translate these fundamentals to perovskite crystallization and grain growth. We further explored the conversion and degradation of the perovskite phases through the printing process, which plays a significant role in device performance, through in situ photoluminescence microscopy, as well as verification through X-ray diffraction. Verification of the observed grain sizes and morphology was also done through scanning electron microscopy, to ensure optical measurements and analysis were accurate. With efficiencies of perovskites approaching current industry standards of silicon, perovskites are increasingly becoming the clear answer to solar industry demands. This research is essential in enabling scalable methods with the potential to revolutionize the solar industry with large scale fully printable devices.

This project deals with human robot-network collaboration for synchronization to desired reference velocities. A human interacts with the network of mobile robots by sending virtual source inputs to the leading robot. The information propagates through the network from each robot sensing its nearest neighbor. This research proposes a visual interface design to develop a real time, wireless communication channel between a human operator and the robot-network. The model developed introduces real time feedback from the human operator via a graphical interface of the relative positions of each robot in the network. The human operator’s ability to move the network cohesively with desired velocity trajectories require rapid information transfer, which is achieved using a delayed self-reinforcement (DSR) technique. We expect the human operator’s ability to move the network cohesively to improve with DSR hence enabling easier operation for the operator. The human-swarm interface designed has applications for semi-autonomous networks such as vehicle platoons. We can improve modern freight transportation safety and efficiency with a human remotely operating a robot-network of trucks.

Small insect-inspired robots have much potential in exploration and have been experiencing a wave of innovation in recent years. Small robots have promise especially in space exploration where each kilogram costs $10,000 to launch, but tiny robots tend to weigh under a gram. However, some problems persist, such as difficulty with landing after flight and hopping mechanisms wearing down after a few uses. Our work focuses on developing a hopping robot that is capable of attaching to an overhanging surface when it jumps and that has durable mechanisms to optimize the number of jumps per bot. The hooking mechanism differs from previous work, usually electrostatic patches, and instead is inspired by the hooked feet of beetles, which is lighter and does not require constant electrical power. For optimizing jumps, we are working to develop a jumping body constructed from and designed for carbon fiber rather than the previously used fiberglass. Carbon fiber has a higher strength to weight ratio and is more elastic than fiberglass, making it efficient for flight and the repetitive motion carried out by the body when bent by the onboard actuator. All designs are created using an iterative design process where parts are micromachined and assembled, then tested for desired qualities. From this, we are aiming to develop an autonomous hopper capable of completing multiple jumps and grabbing without maintenance on any part of the bot.

The formation of dental biofilm (plaque) is promoted through the consumption of dietary sugars, which serves as a precursor to the metabolic process that bacteria must undergo. Organic acids are byproducts of this metabolism, and encourage the demineralization of the enamel which if left untreated leads to formation of dental caries (tooth decay). Evaluation of the acidity of plaque deposits on patient’s teeth can be used as a preventative measure to allow dentists to detect areas vulnerable to dental decay. A ratiometric fluorescence pH sensing device has been developed using an FDA approved dye, Fluorescein, and blue LED excitation. Fluorescent spectral profiles were collected using a spectrometer and analyzed with a spectral unmixing algorithm for calibration over the pH range of 4.5-7, the ideal range to measure the acidic environment of the mouth. A 420 nm LED housed with an electronic driver served as the fluorescein excitation source. Spectral profiles were collected within the 450-650 nm range. In an in vivo pilot study, we found that the dye solution which consists of fluorescein powder and deionized water causes retention issues on interproximal areas. In order to achieve accurate results from the spectrometer, the fluorescein dye must penetrate and diffuse through the dental plaque. To allow enough time for the fluorescein solution to adhere, glycerol was added to increase viscosity. Tests were performed to evaluate the effect of the glycerol addition on the spectral data. Solutions ranging from 0%-50% glycerol were measured. Glycerol addition increases the peak wavelength of the spectra by no more than 1%. The pH of the solution has no effect on this trend. An in vivo case study was performed for high caries risk patients to validate the device. The pH device has the potential to predict early caries, reducing oral restorative procedures and dental expenses.

Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM) have great potentials in biomedical research and can be used extensively in drug screening and heart simulations. To understand the cardiomyocytes, we need to perform functional analysis on these muscle cells. Therefore, we need a simple, controllable, yet biocompatible and high throughput tool to measure the cellular traction force. At the Sniadecki Lab, we are developing a new technique to measure the force generation of hiPSC-CM: dotted traction force microscopy platform. To create the platform, fluorescent proteins were first absorbed to a dotted polydimethylsiloxane (PDMS) negative and stamped onto a polyvinyl alcohol film. The film was then transferred to a soft PDMS substrate and subsequently dissolved using phosphate buffered saline solution while the patterned fluorescent proteins stained the substrate. Since the stiffness of the soft PDMS substrate is known, the force generation of the cardiomyocytes can be calculated in real time by optically tracking the deformation of the fluorescent dots. Currently, we are able to manufacture the platform with high fidelity and uniform alignment with a production time of less than 2 hours. Moreover, the cardiomyocytes can fully spread out to their in vivo state on the substrate which ensures the force measurement is valid and accurate. Potentially, this method is not limited to cardiomyocyte research and can be applied to study the interaction between force generation and cell performance of other cells. We are also exploring the possibility of automated manufacture and integration with 96-well to enable mass production.

My research has worked to develop an automated system that utilizes techniques that will modernize pathology and reduce diagnosis times from days to hours. The current method of diagnosing cancer (histopathology) requires a tissue biopsy that is fixed with formalin for 6-72 hours, dehydrated and embedded with wax, then manually sectioned, mounted on slides, and stained for imaging. This manual process is extremely time and labor-intensive and is the reason diagnoses can take up to ten days. The preferred, and least invasive, way to obtain tissue from a patient is the core needle biopsy (CNB), which is taken by inserting a needle into a region where cancer is suspected to exist, and removing a cylindrical section of tissue. Although CNBs are rapidly becoming the standard-of-care, their small diameters make it difficult to prepare and section the tissue for use in conventional histopathology. My research project over the past year has been to develop CoreView, a device designed to handle CNBs, automatically staining and imaging their entire surface for more complete images used to diagnose cancer. We use deep ultraviolet light to image the outer 2-3 cell layers of fluorescently stained tissue in a lab-built microscope to produce sharp images that can be equivalent to standard histology images from thin sections. I used LabVIEW to develop the rotational and imaging control to image the tissue at different focal points so the biopsy surface stays in focus during rotation. Along with designing necessary components of our system, I have worked on improving processing techniques for staining fixed porcine liver to produce clearer images with high contrast between the nuclei and the cytoplasm/cell boundaries. Our collaborating pathologist has confirmed that these images are at diagnostic quality, proving that CoreView and my improved techniques for processing tissue have the opportunity to revolutionize current histopathology.

This work describes an inexpensive and accurate gesture control implementation designed for an industrial setting. Sensing hand movements and being able to remotely operate devices without use of a tangible control can be useful, particularly in manufacturing applications where other methods of communication may not be available. One gesture recognition method is to use a camera or set of cameras to capture the motions of the user. However, this method imposes line-of-sight workspace constraints and is sensitive to environmental factors, such as consistent lighting conditions. My approach is to use an instrumented glove that detects the amount of bend in specific joints and sends those positions to a central processor that is programmed to recognize control gestures. Similar glove controllers are available but are either not well suited to an industrial setting because the sensors are vulnerable to metal dust and debris, or are not accurate enough to identify commands quickly and consistently. My version has custom sensors exactly fitted to this application and aims to have all sensors sealed and self contained to protect against contamination. This system is able to capture high resolution movement from the wearer and either save that data for machine training or send it immediately to be acted on. Going forward, onboard capabilities such as local gesture recognition will be added, as well as allowing the user to add custom gestures suited to their particular application.

Food contamination outbreaks have become increasingly prevalent in the United States. Food processing companies often do not have sufficient resources to accurately monitor pathogenic bacteria and biofilms on their food preparation surfaces. Unfortunately, consumers assume that the food is safe because it is packaged and ‘screened’ but invisible bacterial contamination may be present. This creates an opportunity to improve methods for detecting pathogenic bacteria in food handling and processing environments. BioVizia provides an alternative solution for detecting pathogenic bacteria on food processing surfaces that is efficient yet effective. We have developed a device that uses an LED to excite a fluorescent dye. Fluorescein is an FDA approved dye that exhibits pH dependent spectral properties. When viable pathogenic bacteria metabolize sugar, they produce acidic byproducts. Therefore an optical system using fluorescein as a pH disclosing agent may provide sufficient sensitivity for detecting bacterial contamination. Our optical system records the fluorescein emission spectra which contains two overlapping, pH dependent spectral features. The fractional amount of the two contributing bands are calculated using a spectral unmixing algorithm. A calibration with standardized pH buffers yields a linear relationship between pH and the fractional amount of each band. This noncontact optical pH measurement method has been successfully employed in an in vivo dental study to measure the pH drop produced by dental plaque following a sucrose rinse. We seek to demonstrate that BioVizia can make the detection of pathogenic bacteria and biofilms on food preparation surfaces fast and quantitative.

Manipulating airflow over aerodynamic surfaces with plasma, compressed air jets and textured surfaces has become an area of intense aeronautical research and international competition in the last few years. Electrohydrodynamic (EHD) thrusters or plasma actuators have been demonstrated as remarkable devices for separation control and lift enhancement. The application of EHD thrusters to an aerial vehicle can drastically reduce the power consumption, weight and response time of mechanical controls. The focus of the present work is to determine the performance of a full-scale aircraft wing with an integrated corona discharge driven EHD thruster numerically. The numerical model is carried out by coupling the interactions between fluid mechanics and electrostatics. The study has been conducted on an augmented NACA 0012 airfoil with trailing edge flaps at a Reynolds number of 160,000 (10m/s). The EHD induced jet delays separation while lengthening and flattening the separation region. Preliminary results show that the actuator has increased the moment on the airfoil by 50% which helps in better maneuverability. The numerical results are compared with the experimental wind tunnel results. These findings can favor a strong design of a new generation energy-efficient aircrafts

Medical imaging techniques such as X-ray, provide clinicians intensive information on the disease/condition of patients. However, clinicians have to look away from the subject to refer to medical images, thereby losing track of their work. Thus, clinicians usually study the images prior to surgery and limit reference time to images during surgery. Furthermore, unlike X-ray, novel imaging methods (such as optical ultrasound) are not taught in medical schools, so untrained clinicians face challenges in interpreting the images. These two limitations restrict the clinicians’ ability to fully utilize and adopt advanced medical imaging techniques. In this work, we explore the possibility of using Augmented and Virtual Reality (AR/VR) in the context of medical imaging. Prior applications of AR/VR technology in medicine have been limited to AR-aided training for medical students, telepresence for interaction, as well as remote therapy. We aim to use AR as a real-time diagnostic and therapeutic tool by augmenting the clinicians’ live view with various imaging modalities (such as X-ray, optical ultrasound, near-infrared). We hypothesize that providing these images in-context, and in some cases aligned with the subject, will improve the interpretation of images resulting in better guidance for diagnosis or surgery. To test this, we are creating an AR-based medical imaging/analysis application that uses techniques such as volumetric rendering and real-time image registration to augment the clinicians' view. Furthermore, clinicians can interact with the images by filtering, slicing, and reducing dimensionality, in order to better understand the images and thereby the underlying disease/condition.

Supraspinatus tendon tears are a type of rotator cuff tear, accounting for 15% of overhead workplace musculoskeletal injuries. These tears disproportionately affect blue-collar workers and cost millions in healthcare every year, but there is still relatively little known about the appropriate work-rest cycles to prevent the risk of occurrence during work. Directly measuring the rotator cuff in vivo is difficult because the supraspinatus is covered by the bursa sac, the acromion, and the deltoid, making its material properties hard to accurately record. This presents a need for a material that can model an in vivo shoulder tendon. There are many options of what materials can be used: organic and in vitro models are the most common, with relatively new inorganic models being designed. However, none of these models fulfill all modeling needs; overlap between all models is needed to get an idea of how an in vivo tendon accumulates damage. Organic models can provide tissue repair and degradation rates and these can be projected for a human supraspinatus. From in vitro studies stress-strain curves and maximum load can be recorded, and from inorganic models tear propagation can be observed. This work compiles research on candidates for tendon proxy materials by cross-referencing a variety of papers in tendon literature to find the foundational papers. Then builds off those with other works by the foundational authors or other highly regarded works that cite those foundational papers. From the collection of these papers, the shortcomings of current tendon modeling can accurately be seen, showing what research is needed to better model in vivo tendons. For instance, to confirm the hypothesized projection from organic models, psychophysical testing that isolates the supraspinatus needs to be conducted. Better modeling of tendons will allow for better prediction of appropriate work-rest cycles that may slow tendon fatigue damage.

Platelets seal wounds in blood vessels in order to prevent blood loss. When there is an exposed vascular matrix, platelets bind at the wound site through the glycoprotein (GP) Ib-IX-V complex. Glycoprotein receptors allow platelets to initiate homeostasis by forming attachments to the damaged tissue. Platelets use their glycoprotein receptors to form bridges between other platelets and the surrounding proteins that form the clot within the blood vessel. Aspirin, a common household medication, produces its effects through inhibition of thromboxane production which prevents the formation of these blood clots by meddling with platelet aggregation. Standard doses of aspirin for an adult are 81mg, 325mg, and 500mg. However, there could be differences between male and female platelets, indicating that there may be different amounts of glycoprotein receptors between males and females. Here, we evaluated the force of single platelets without aspirin in males and females and single platelets with aspirin in males and females by using a reference-free traction force microscopy (TFM) platform. This TFM platform contained a grid of a fluorescent protein at known locations and was coated with von Willebrand Factor (VWF) to mediate platelet binding. Immunofluorescent staining and fluorescent imaging was conducted to visualize to platelet f-actin, a cytoskeletal component, and GPIb. Platelet binding, spreading, and contraction is observed on these substrates. By placing the platelets on the substrate, we are able to measure the deflection of the grid and determine the force a single platelet generates. In the future, we hope to measure the force of platelets at 0mg, 81mg, 325mg, and 500mg between men and women and hope to elucidate how GPIb expression, platelet mechanics, and response to aspirin varies in males and females.

Manufacturing workers are often subjected to many rigorous and repetitive shoulder and arm motions, usually leading to shoulder injuries. Assessing the likelihood of an injury before it occurs and adjusting practices accordingly can keep the individual from the severe pain that shoulder injuries can cause. This research focuses on creating such a predictive model to warn individuals before they sustain an injury. I created a mathmatical model to assess critical positions that would cause the most stress in the shoulder joint. A Kinect sensor locates the arm joints in space and my Matlab code calculates the expected reaction forces in the shoulder. My current results focus on single, static positions defined by common industry working positions. Future work will focus on dynamic positions and comparing the results from the mathematical model with biological indicators to determine if this predictive model is indicative of injury.

Efforts to engineer flying micro-robots (~50mg) are motivated by their potential advantages relative to larger robots, such as greater deployment numbers at the same cost. There are significant developments in flapping wing robots at insect-scale; however, little advancement has been made in the development of robots with ionic actuation using electrohydrodynamic (EHD) thrust. This thrust is generated through the ionization of air particles and momentum transfer of these positive ions with neutral air molecules. EHD thrusters have used collector grids and emitter wires to generate a thrust for controlled flight. In this research, we design and fabricate a 1.8 x 2.5 cm micro-thruster that weighs a total of 43 mg including the carbon fiber collector grid, four blue tempered steel emitters, and eight fiber optic glass tubes. This robot is hand-assembled using a laser fabricated external fixture. Electrodes of the robot are fabricated using a laser based system. The whole robot takes a total of 20 minutes to assemble. Emitters are supplied with a high voltage (~2.5kV) using a bundle of 51-gauge insulated copper wires. Similar wire is used for grounding the collector grid. A parametric study is carried out to optimize the physical parameters of the robot. Experiments performed in this research show that the thrust generated is larger than the weight of the robot. 

This research is aimed at improving the functionality and use of multi-robot control through several different aspects. One important aspect of this project is collision avoidance between multiple ASEA Brown Boveri (ABB) industrial robots. The active collision avoidance software is an efficient tool that detects potential collisions between multiple robots working in collaboration and the surrounding cell. The user can specify a safety net around each robot, which notifies the user if one or more robots are on a collision course. Each robot’s position is graphically displayed to the screen with respect to the user-defined world coordinate system, complete with logs of tool center point positions and time stamps, so collisions can be reproduced. This software is intended to be used in conjunction with automated scheduling as an external safety checker. Another important aspect of this research is the end effector, an attachment that is secured onto the end of the ABB robot and used to drill a series of holes in a given surface. The end effector has gone through numerous design improvements through which it became smaller and more cost efficient. The latest design incorporates the addition of a raspberry pi, a small single-board computer, which serves as a failure test. The pi is programmed to generate random failures which notifies the user to take the robot out of the running program. This system will eventually be used to detect real robot failures and alert the user of the malfunction. The end effector also has a separate attachment which is used to hold a camera in order to incorporate machine vision into the multi-robot system. Adding machine vision helps robot position calibration, along with detecting foreign objects other than the moving robots in the robot cell. This addition also improves security and liability of the system.